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標題: | 智慧電網高壓輸電線之動態熱容量估算與風險管理評估 Dynamic Thermal Rating Estimation and Risk Management Assessment of HV transmission lines in Smart Grid |
作者: | Shih-Syuan Hong 洪士軒 |
指導教授: | 江昭皚(Joe-Air Jiang) |
關鍵字: | 智慧電網,動態熱容量,輸電線溫度,風險管理評估,垂度, Smart grid,Dynamic thermal ratings,Transmission temperature,Risk management assessment,sag, |
出版年 : | 2021 |
學位: | 碩士 |
摘要: | 本研究將風險管理評估應用於高壓輸電線上,並估算未來一天動態熱容量,提前得知可調配的載流量狀況。有鑑於輸電線線路導體溫度對於輸電安全及提升輸電效益的重要性,然而輸電線線路溫度及線路電流資訊現階段的作法皆由IEEE Std 738-2012標準規範的動態額定熱容量公式推估而來,其估計值的正確性攸關著輸電安全,是為輸電系統安全評估的一大重要課題。由氣象局提供的氣候資訊(風速及環境溫度)做為IEEE Std 738-2012標準規範中動態熱容量方法所推估出的估計值,其中環境溫度由過去一個月進行統計分析得出未來一天可能溫度範圍,風速則是透過機器學習方法由過去12小時風速得到未來3小時風速,再將此結果套入IEEE Std 738-2012標準規範可以得到未來一天動態熱容量範圍,再將最低點減去100安培,此值視為最大可調配額定值,結果顯示出此方法有95%不會造成輸電線損壞又能提高輸電容量,並且用導體溫度及輸電線垂度驗證此次提高電流並不會造成損壞。 為了最大程度減少危害,所以透過風險管理評估,將輸電線進行導體損壞概率的計算,進而準確判斷出損壞概率,提前作出對策。導體損壞概率主要使用應力模型及老化模型,並由韋伯分布函數將此兩模型結合,將經驗參數訓練完後,只需將導體溫度代入,即可得知損壞概率。本研究表明輸電線路上的導體溫度與氣象參數息息相關,甚至與其所能負載的電流容量皆有重大影響,在輸電安全評估上亦與氣候參數有著密不可分的關係。透過風險管理評估確保輸電安全性,透過風險管理評估可提前規劃未來狀況,避免因為錯估輸電額度導致安全事故產生。 In this research, risk management assessment is applied to high-voltage transmission lines, and the dynamic thermal rating of the next day is estimated, and the adjustable current carrying capacity is known in advance. Because of the importance of the conductor temperature of the transmission line to the safety of power transmission and the improvement of the efficiency of power transmission, the current practice of the temperature and line current information of the transmission line is derived from the dynamic rated thermal rating formula of the IEEE 738-2012 standard. The correctness of its estimated value is critical to the safety of power transmission and is an important subject for the safety assessment of power transmission systems. The climate information (wind speed and ambient temperature) provided by the Bureau of Meteorology is the estimated value estimated by the dynamic thermal rating method in the IEEE 738-2012 standard specification, in which the ambient temperature is statistically analyzed in the past month to obtain the possible temperature for the next day The wind speed is the wind speed in the next 3 hours from the wind speed in the past 12 hours through the machine learning method, and then the result is inserted into the IEEE 738-2012 standard specification to get the dynamic thermal rating range for the next day, and then the lowest point is subtracted by 100 amperes. This value is regarded as the maximum adjustable rating. The results show that 95% of this method will not cause damage to the transmission line and increase the transmission capacity, and the conductor temperature and the sag of the transmission line are used to verify that the current increase will not cause damage. To minimize the damage, the risk management assessment is used to calculate the probability of conductor damage to the transmission line, and then accurately determine the probability of damage, and make countermeasures in advance. The conductor damage probability mainly uses the stress model and the aging model, and the Weber distribution function combines these two models. After training the empirical parameters, just substitute the conductor temperature to know the damage probability. This study shows that the conductor temperature on the transmission line is closely related to the meteorological parameters, and even has a significant impact on the current capacity it can load. It is also closely related to the climatic parameters in the transmission safety assessment. Through the risk management assessment to ensure the safety of power transmission, the future situation can be planned to avoid the occurrence of safety accidents caused by the misestimation of the transmission quota. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73894 |
DOI: | 10.6342/NTU202100216 |
全文授權: | 有償授權 |
顯示於系所單位: | 生物機電工程學系 |
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